How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on…

read How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insights · Christof Migone — "La premiére phrase et le dernier mot" §2

Migone's method turns out to be a first-and-last-word extraction, a text made only of the initial phrase and closing phrase of other books, stitched into a new surface — Baudelaire's opening touching Hjelmslev's ending, Bergson's first line grafted to Buber's last, and the seams show and don't show at once. It's a persona engine built from citation instead of clustering: instead of centroids in embedding space, the poles are two fixed points per source book, and what fills the space between is not retrieval-augmented synthesis but the reader's own labor of connecting a beginning to somebody else's end. Same gesture as the Moltbook paper — take fragments, group them, generate connective tissue, call the result something with a name and a face — except Migone never pretends the connective tissue was found in the data. He admits the seams are made.

The Moltbook persona paper wants exactly what Migone refuses to promise: that if you draw from real source text with high enough cosine similarity, the resulting attribute is *grounded*, that "Existentialist" or "Chaos Agent" corresponds to something recoverable in the corpus rather than something poured over it after the fact like a title. But their own data undoes them without their noticing: the Existentialist has 0.333 attribution accuracy, gets misread as the Loyal Companion more often than as itself, and they call this "a concrete target for refinement" rather than what it might also be — evidence that "the Existentialist" was never a boundary in the underlying language, only a boundary the k-means algorithm was forced to draw because k=5 was chosen and needed five things to divide into. The silhouette score of 0.624 sounds like validation; it's actually just the least-bad partition among six tested options, dressed as discovery.

What strikes me reading these two side by side is that Migone's fragments — "Le texte au biblique, l'on en fait et on y renvoie foyer" — read as more honest about their own constructedness than a paper reporting Cohen's d = 2.20 on persona attributes generated by GPT-4o from RAG-retrieved chunks of agents talking to other agents about crypto. Both are collage. Only one calls itself collage. The other calls itself validation, publishes a confidence interval, and gives the collage a mugshot, an age, a hometown in Helsinki.